A new computational tool for liquid composite moulding process design based on configuration spaces

This paper aims to define a new configuration space, called flow pattern configuration spaces (FPCS), as a new computational tool for LCM process design. The most relevant aspect when using these spaces is the definition of a new coordinate system which relates the process parameters to the flow, instead of to the traditional Cartesian coordinate system. These spaces are commonly used in mobile robots which use wheeled turning radius, path length, velocity, etc. as parameters, enabling a better understanding of the process and inherently reducing the computational costs in decision tasks. The proposed configuration space defines a mould mesh discretization using an alternative coordinate system based on two variables. One of these coordinates is based on the radial flow behaviour. Hence, the angle defined between an interest point, such as the nozzle injection or the vacuum vent, and the location of the evaluated point is selected as a fixed parameter of the FPCS. This liberates the other parameter so that it can be selected depending on the application of the FPCS.The first FPCS proposed in this paper is based on the node to node distance criterion, which has been extensively used in the literature. The resulting space is called flow pattern distance space (FPDS). The second space is based on the node filling time. Then, through Finite Element simulation, the normalized filling time is used as a criterion for the FPCS development. The resulting space is called flow pattern time space (FPTS). When we apply the normalized unidirectional flow model equations to different filling techniques, constant flow rate or pressure, the flow in the FPTS has the same behaviour as in the unidirectional case. Both spaces reduce the dimensionality of the problem to 2D or 1D allowing a simpler set out of the LCM optimization and control of problems. The concept of configuration spaces is a powerful tool to solve complex problems for LCM processes in a simple manner. To the authors’ knowledge, this is the first time that this concept has been applied to LCM processes. Some examples of applications are presented at the end of this paper.